Isbn: 9786630368697 - semi-supervised graph learning for drug-drug interaction prediction (4 Ergebnisse)

Taschenbuch. Zustand: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware 56 pp. Englisch.

Taschenbuch. Zustand: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - This book proposes a Semi-Supervised Graph Learning framework for Drug-Drug Interaction Prediction, designed to overcome the limitations of traditional supervised learning methods that require large quantities of labelled interaction data. The proposed approach effectively integrates both labelled and unlabeled drug information, enabling the model to learn meaningful patterns even when only a limited number of known interactions are available. Each drug is represented using comprehensive feature information, including molecular structures, chemical descriptors, pharmacological properties, and existing interaction networks. These features are incorporated into a graph-based representation that preserves the intrinsic relationships among drugs. A Graph Neural Network is then employed to perform message passing and neighborhood aggregation, generating low-dimensional embedding vectors that capture both the structural and semantic characteristics of each drug within the interaction network. These learned embeddings are subsequently used to predict previously unknown or potential drug-drug interactions with improved accuracy.…

Taschenbuch. Zustand: Neu. This item is printed on demand - Print on Demand Titel. Neuware 56 pp. Englisch.

Taschenbuch. Zustand: Neu. Semi-Supervised Graph Learning for Drug-Drug Interaction Prediction | Suryakanthi Tangirala (u. a.) | Taschenbuch | Englisch | 2026 | LAP LAMBERT Academic Publishing | EAN 9786630368697 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu Print on Demand. …